Building of Informatics, Technology and Science (BITS)
Informatics
Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. This journal is managed by Forum Kerjasama Pendidikan Tinggi (FKPT) published 2 times a year in Juni and Desember. The existence of this journal is expected to develop research and make a real contribution in improving research resources in the field of information technology and computers.
Articles in this Journal
Machine Learning Comparative Analysis of SVR Method with RBF Kernel and Random Forest for Bitcoin Price Prediction
This study aims to determine how accurate machine learning predictions are for predicting Bitcoin prices using the SVR With RBF Kernel and Random Forest methods. This study was conducted because Bitcoin’s volatility is so high that it is difficult to...
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Market-Adaptive Stock Trading through B-WEMA Driven Proximal Policy Optimization
Developing automated trading strategies that achieve stable returns while controlling risk remains a central threat in quantitative finance. Many reinforcement learning-based trading systems focus on reward maximization but provide limited justificat...
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Analisis Kinerja Decision Tree dan Naïve Bayes Pada Klasifikasi Tingkat Kepuasan Masyarakat
The Public Satisfaction Survey (SKM) is an official instrument used by the government to evaluate public service performance as stipulated in Regulation of the Minister of State Apparatus Empowerment and Bureaucratic Reform (PermenPANRB) Number 14 of...
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Optimasi Hyperparameter Random Forest untuk Klasifikasi Depresi Mahasiswa Menggunakan GridSearchCV dan RandomizedSearchCV
Student mental health is an important issue that requires a data-driven approach to support the classification process of student depression. This study aims to analyze the factors that cause depression and optimize the performance of the classificat...
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Deep Fake Image Detection Using Vision Transformer with Random Oversampling Technique
Recent developments in deep learning have facilitated the generation of visually convincing deepfake images, creating serious concerns for the reliability and security of digital media content. The primary challenge lies in detecting these sophistica...
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Deteksi Cyberbullying pada Komentar Media Sosial Berbahasa Indonesia Menggunakan Pendekatan Hibrida IndoBERTweet- BiLSTM
Cyberbullying on Indonesian-language social media has become a serious issue with significant psychological and social consequences, necessitating the development of reliable automated detection systems. However, the informal, ambiguous, and highly c...
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Klasifikasi Kesehatan Mental Menggunakan Support Vector Machine Berdasarkan Screen Time dan Interaksi Sosial Digital
Mental health is an important aspect that influences the quality of life of individuals, especially in adolescents and young adults who are vulnerable to stress due to the increased use of digital devices. Technological developments have led to incre...
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Implementasi Deep Learning Berbasis MobileNetV2 untuk Deteksi Real-Time Bacterial Spot dengan Pendekatan Arsitektur Lightweight
Bacterial spot caused by Xanthomonas campestris pv. vesicatoria is a critical disease in bell peppers that can reduce productivity by up to 50%. This study implements MobileNetV2 with two-stage transfer learning for real-time bact...
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Performance Analysis of Quantum Long Short-Term Memory (QLSTM) Models for TLKM Stock Price Prediction
Stock price prediction is a challenging task due to its nonlinear, dynamic, and temporal characteristics, yet accurate forecasting models are crucial for decision-making in volatile stocks such as PT Telkom Indonesia Tbk (TLKM). Despite the rapid ado...
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Analisis Sentimen Diseminasi Produk Iklim Menggunakan Metode Recurrent Neural Network (RNN) dalam Klasifikasi dan Density-Based Spatial Clustering of Applications with Noise (DBSCAN) untuk Klasterisasi
Climate change and extreme weather events have a significant impact on various sectors of life, making the accurate and timely dissemination of climate information crucial. Public sentiment can be an indicator of public assessment of climate dissemin...
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Analisis Pola Temporal Penyebaran Penyakit DBD dan HIV Berbasis Time Series Clustering
In Indonesia, including in East Java Province, infectious diseases such as Dengue Fever (DHF) and Human Immunodeficiency Virus (HIV) remain public health concerns. Incidence patterns vary by region and time of year. Variations in temporal patterns am...
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Explainable Aspect-Based Sentiment Analysis with Contrast-Aware IndoBERT for Indonesian Public Service Reviews
This study presents an Explainable IndoBERT with Contrast-Aware Attention framework for Aspect-Based Sentiment Analysis (ABSA) on Indonesian public service reviews. The proposed model integrates automated aspect labeling using KeyBERT with a contrast...
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Penerapan Algoritma Naïve Bayes Terhadap Sentimen Ulasan Produk Skincare Pada E-Commerce Shopee
The rapid growth of the beauty industry has generated a large volume of consumer reviews, necessitating an automated processing system to understand public sentiment. This study aims to implement sentiment analysis on skincare product reviews using t...
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Stacking-Correspondence Analysis for Fuzzy Data: Computational Framework for Analyzing Complex Qualitative Survey Data
Bandung Regency faces a significant challenge in achieving Sustainable Development Goal (SDG) 12, marked by a critically low score of 14.53 out of 100. Uniform policies are often ineffective due to regional diversity and uncertainty in categorical su...
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Reversible Data Hiding Citra MRI T1-Weighted Menggunakan Spatial Fuzzy C-Means dan Selective Histogram Shifting
The transmission of medical images over telemedicine networks increases the risk of data leakage and manipulation of sensitive information. This study develops a Reversible Data Hiding framework that integrates Spatial Fuzzy C-Means, Selective Histog...
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